Particle size distribution determination from spectral extinction using neural networks

The use of techniques based on spectral extinction to recover particle size distributions has become increasingly popular in recent years. However, they are time-consuming and are not always successful in practical applications. In this paper, a novel method is proposed to determine particle size distributions using neural networks from several spectral extinction measurements. Simulations and experiments have illustrated that it is feasible to use a neural network to obtain the parameters of a particle size distribution from turbidity measurements. Although the neural network was trained using log-normal distribution data, it can be used to recover some non-log-normal distributions. The method has advantages of simplicity of use, instantaneous delivery of results, and suitability for online particle size analysis.